JuliaLang/julia

Documentation
Continuous integration
Code coverage

Julia is a high-level, high-performance dynamic language for technical computing. The main homepage for Julia can be found at julialang.org. This is the GitHub repository of Julia source code, including instructions for compiling and installing Julia, below.

• Homepage: https://julialang.org
• Install: https://julialang.org/downloads/
• Source code: https://github.com/JuliaLang/julia
• Documentation: https://docs.julialang.org
• Packages: https://julialang.org/packages/
• Discussion forum: https://discourse.julialang.org
• Zulip: https://julialang.zulipchat.com/
• Slack: https://julialang.slack.com (get an invite from https://julialang.org/slack/)
• YouTube: https://www.youtube.com/user/JuliaLanguage
• Code coverage: https://coveralls.io/r/JuliaLang/julia

We welcome contributions from developers of all experience levels, including bug fixes, documentation improvements, tests, and performance enhancements.

New contributors are encouraged to start by reading CONTRIBUTING.md.

• Learning resources

The recommended way of installing Julia is to use juliaup which will install the latest stable julia for you and help keep it up to date. It can also let you install and run different Julia versions simultaneously. Instructions for this can be found here. If you want to manually download specific Julia binaries, you can find those on the Manual Downloads page. The downloads page also provides details on the different tiers of support for OS and platform combinations.

If everything works correctly, you will get a julia program and when you run it in a terminal or command prompt, you will see a Julia banner and an interactive prompt into which you can enter expressions for evaluation. You can read about getting started in the manual.

Note: Although some OS package managers provide Julia, such installations are neither maintained nor endorsed by the Julia project. They may be outdated, broken and/or unmaintained. We recommend you use the official Julia binaries instead.

First, make sure you have all the required dependencies installed. Then, acquire the source code by cloning the git repository:

git clone https://github.com/JuliaLang/julia.git

and then use the command prompt to change into the resulting julia directory. By default, you will be building the latest unstable version of Julia. However, most users should use the most recent stable version of Julia. You can get this version by running: (replace [tag] with the desired tag)

git checkout [tag]

To build the julia executable, run make from within the julia directory.

Building Julia requires 2GiB of disk space and approximately 4GiB of virtual memory.

Note: The build process will fail badly if any of the build directory's parent directories have spaces or other shell meta-characters such as $ or : in their names (this is due to a limitation in GNU make).

Once it is built, you can run the julia executable. From within the julia directory, run

./julia

Your first test of Julia determines whether your build is working properly. From the julia directory, type make testall. You should see output that lists a series of running tests; if they complete without error, you should be in good shape to start using Julia.

You can read about getting started in the manual.

Detailed build instructions, should they be necessary, are included in the build documentation.

By default, Julia does not install anything outside the directory it was cloned into and ~/.julia. Julia and the vast majority of Julia packages can be completely uninstalled by deleting these two directories.

The Julia source code is organized as follows:

The Julia REPL is quite powerful. See the section in the manual on the Julia REPL for more details.

On Windows, we highly recommend running Julia in a modern terminal, such as Windows Terminal from the Microsoft Store.

Support for editing Julia is available for many widely used editors: Emacs, Vim, Sublime Text, and many others.

For users who prefer IDEs, we recommend using VS Code with the julia-vscode plugin.
For notebook users, Jupyter notebook support is available through the IJulia package, and the Pluto.jl package provides Pluto notebooks.